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Suganthan-Mohanadasan

Google Search Console MCP Server

by Suganthan-Mohanadasan
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image_pages_overview

Rank pages by Google Images search performance, revealing which pages surface in image results and which do not. Use impressions, clicks, and position data to identify pages needing optimization.

Instructions

Pages on the site ranked by image-search performance. Tells you which pages are actually surfacing in Google Images and which are not. Pairs with image_keyword_overview to map ranking queries back to the pages carrying them. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of days to analyse
order_byNoSort fieldclicks
site_urlNoOverride the configured property (e.g. sc-domain:example.com or https://www.example.com/)
row_limitNoMaximum rows to return
min_impressionsNoMinimum impressions threshold

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.5.1
    • addedInput schema / properties / site_url
      Added value: +{
+  "description": "Override the configured property (e.g. sc-domain:example.com or https://www.example.com/)",
+  "type": "string"
+}
  2. Addedv2.4.0

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations present, the description carries the full burden and does so extensively. It discloses that position is an impression-weighted average, not a rank-tracker rank, that deep positions rest on sparse data, and that absolute values should be treated as directional with preference for period-over-period deltas. It also instructs the agent not to speculate beyond the data, adding crucial interpretation guardrails.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than average but every section earns its place: purpose, sibling pairing, analysis rules, presentation requirements, and position caveats. The labeled IMPORTANT, PRESENTATION, and POSITION blocks make the content scannable and front-load the most critical operational constraints.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotation safety profile, so the description must fully equip the agent; it does. It explains what the tool identifies, how to interpret the core metric (position), how to handle uncertainty, and how to present results. While it does not list return fields verbatim, the schema's order_by values and the instruction to report exact numbers make the expected output shape reasonably inferable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3; the schema already documents all five parameters. The description adds meaningful nuance about the `position` field and its interpretation, which relates to one of the `order_by` enum values, but it does not add semantics for `days`, `row_limit`, `min_impressions`, or `site_url` beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: pages ranked by image-search performance, and clearly states the outcome — identifying which pages surface in Google Images and which do not. It also distinguishes itself from image_keyword_overview by explaining the pairing relationship, so an agent can separate page-level from keyword-level analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when this tool is appropriate: page-level image-search performance, with explicit pairing to image_keyword_overview for mapping queries to pages. It does not explicitly enumerate when not to use this tool relative to other siblings like image_page_audit or image_search_quick_wins, so it stops just short of full exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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